The Scale Law and Growth Limits of the Crypto Assets Ecosystem

With the rapid development of artificial intelligence, large model technology is expanding at a rate faster than Moore's Law, driven by capital. This phenomenon has also prompted reflections on the development patterns of the blockchain industry. As a certain L2 network enters the coin issuance phase and Ethereum returns to L1 competition, we might as well borrow the concept of scaling laws to explore the rise limits of the Crypto Assets ecosystem.

The Data Scale of Full Nodes on Public Chains

Full node data is an important indicator of the scale of public chains. As of now, the full node data of a certain high-performance public chain has reached 400TB, far exceeding Ethereum's 13TB and Bitcoin's 643.2GB. This data volume reflects the balance between decentralization and consensus efficiency.

The founder of Bitcoin considered Moore's Law at the design stage, strictly limiting data growth below the hardware expansion curve. This decision appeared quite prescient, as Moore's Law is now nearing its limits. Whether it's CPU, GPU, or storage technology, there is a trend of slowing growth.

Faced with this dilemma, Ethereum chooses to focus on ecological optimization and reconstruction, striving to seize the initiative in the trillion-scale tokenization of physical assets. On the other hand, a certain high-performance public chain pursues extreme transaction speeds, but its massive node scale has already excluded ordinary users from participation.

The Scale Limit of the Token Economic System

Although the artificial intelligence field has not been able to deeply integrate with Crypto Assets as expected, this has not hindered the rise of certain projects' coin prices. Based on the current market performance, we can roughly estimate that the scale limit of public chain economic systems is around $300 billion.

Drawing on the concepts from the book "Scale", we can observe the phenomena of "super-linear scaling" and "sub-linear scaling" in the Crypto Assets market. For example, the rise of Ethereum from 1 dollar to 200 dollars is faster than its growth from 200 dollars to its historical high.

The Evolution of DeFi Yield

DeFi, as an important application in the blockchain field, has also experienced significant changes in its yield. From the early promise of a 20% annual yield by a certain algorithmic stablecoin project, to the over-collateralization ratio of 150% on a certain decentralized lending platform, and now to the 5.51% 90-day moving average annual yield of a certain stablecoin project, we can see that the overall trend of DeFi yields is declining.

It is worth noting that even if there are trillions of physical assets on the blockchain in the future, it may further reduce the average yield of DeFi rather than increase it. This aligns with the sub-linear scaling law, which states that an increase in system size does not necessarily lead to an improvement in capital efficiency.

Conclusion

Looking at the development history of blockchain, we find that the differentiation trend among public chains has not been eliminated. Bitcoin is gradually becoming estranged from the on-chain ecosystem, while the immaturity of on-chain credit and identity systems has led to the over-collateralization model becoming mainstream. Whether it is stablecoins or the tokenization of physical assets, it reflects the leveraged migration of off-chain assets to on-chain.

Under the existing scale law of blockchain, we may have already reached a growth limit similar to Moore's Law. It has only been 5 years since the explosion of DeFi, and only 10 years since the birth of Ethereum. In the future, how blockchain technology can break through these limitations and achieve new growth will be an important challenge facing the entire industry.